I-Corps: Bio-Inspired Predictive Engineering Analysis Tool

点击翻译按钮获取中文摘要

The broader impact/commercial potential of this I-Corps project is to obtain the benefits available from modernizing legacy processes in the made-to-order design manufacturing industry. Traditionally the mathematical processes used to analyze potential designs are very linear in nature, and do not offer the manufacturer a complete picture of the overall impacts of the non-linear parts of their designs. With the predictive engineering analysis tool developed here, a manufacturing facility can preview the results available from using a particular engineering design prior to the actual manufacturing and testing of the physical parts. Design parameters and environmental conditions can also be inserted into the tool which are then used to better predict the behavior of the part after it is produced. This innovative virtual tool has the potential to be added to the set of existing design and testing tools already being used and let manufacturers predict the success or failure of a part. The impact of this tool would be decreased time to market, eliminating the guesswork now used in certain aspects of a design and saving valuable physical resources.This I-Corps project defines an innovative scalable software tool that is capable of virtually predicting the success or failure of an engineering design prior to production. The technique is based on the mathematical modeling of the coordinated behaviors of biological system. This allows the tool to quickly search and intelligently predict the best solution sets to a multi-objective problem in a given design space. This project employs these innovative bio-inspired techniques to develop algorithms which are applied to engineering designs to produce an ideal set of solutions based on user defined objectives. Bio-inspired algorithms have been shown to improve upon current standard rigid mathematical techniques. This project provides the flexibility to implement an approach that is able to search the entire problem space at once therefore giving better visibility to all of the possible solutions. Since no particular parameter in isolation impacts the outcome of the algorithm, the user is presented with the opportunity to shift the input parameters and rerun the optimization. Further this I-Corps project attempts to explore and define the input parameters for a variety of industries, and assist the end user in coming up with better designs for their products.